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Authors designed the dataset to be used for cloning detection, performed by means of Adobe Photoshop CS3 and Adobe After Effect CS5 [15].
MMH was responsible for miRNAs cloning, detection and drafting the manuscript.
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Bellon created a benchmark set of clones by random sampling and evaluating a random subset of the union of clones detected by all clone detection tools in the study.
Moreover, most existing clone detection techniques focus overly on merely detecting clones and this impairs their ability to accurately find "vulnerable" clones.
Code clone detection is a well-known software engineering problem that aims to detect all the groups of code blocks or code fragments that are functionally equivalent in a code base.
Although numerous techniques and tools have been proposed for code clone detection (Kamiya et al. [2002]), only little has been known about, which detected code clones are appropriate for refactoring and how to extract code clones for refactoring.
Section 2 discusses the literature review for clone detection.
Effective code clone detection will support perfective maintenance.
The results of the code clone detection are presented as clone pairs and clone clusters.
The first tool considered for analysis is the CLAN clone detection with metrics based clone detection technique and method-level granularity.
Section 3 introduces the basic definitions and background details of code clone detection.
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CEO of Professional Science Editing for Scientists @ prosciediting.com